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arXiv Computer Vision By Abolfazl Babanazari, Kaveh Fathian

On Maximum Clique and Maximum Consensus Formulations in Point Cloud Registration

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The paper investigates the theoretical relationship between maximum clique and maximum consensus formulations used in robust point cloud registration. It demonstrates that a maximum clique can incur arbitrarily large alignment error and be much larger than the maximum consensus set at any fixed tolerance, while also deriving geometric conditions that bound this error. The authors provide sharp error bounds for the translation subproblem with fixed rotation, analyze group‑k consistency, and identify the minimal group sizes needed to guarantee alignment error bounds independent of scale and geometry.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Computer Vision.

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